Shanghai Institute for Advanced Immunochemical Studies, ShanghaiTech University, Shanghai, China.
School of Life Science and Technology, ShanghaiTech University, Shanghai, China.
BMC Biol. 2024 Nov 19;22(1):264. doi: 10.1186/s12915-024-02067-w.
For decades, KRAS has always been a huge challenge to the field of drug discovery for its significance in cancer progression as well as its difficulties in being targeted as an "undruggable" protein. KRAS regulates downstream signaling pathways through protein-protein interactions, whereas many interaction partners of KRAS remain unknown.
We developed a workflow to computationally predict and experimentally validate the potential KRAS-interacting proteins based on the interaction mode of KRAS and its known binding partners. We extracted 17 KRAS-interacting motifs from all experimentally determined KRAS-containing protein complexes as queries to identify proteins containing fragments structurally similar to the queries in the human protein structure database using our in-house protein-protein interaction prediction method, PPI-Miner. Finally, out of the 78 predicted potential interacting proteins of KRAS, 10 were selected for experimental validation, including BRAF, a previously reported interacting protein, which served as the positive control in our validation experiments. Additionally, a known peptide that binds to KRAS, KRpep-2d, was also used as a positive control. The predicted interacting motifs of these 10 proteins were synthesized to perform biolayer interferometry assays, with 4 out of 10 exhibiting binding affinities to KRAS, and the strongest, GRB10, was selected for further validation. Additionally, the interaction between GRB10 (RA-PH domain) and KRAS was confirmed via immunofluorescence and co-immunoprecipitation.
These results demonstrate the effectiveness of our workflow in predicting potential interacting proteins for KRAS and deepen the understanding of KRAS-driven tumor mechanisms and the development of therapeutic strategies.
几十年来，KRAS 一直是药物发现领域的巨大挑战，因为它在癌症进展中的重要性以及作为一种“不可成药”的蛋白质的靶向难度。KRAS 通过蛋白-蛋白相互作用调节下游信号通路，而 KRAS 的许多相互作用伙伴仍然未知。
我们开发了一种工作流程，基于 KRAS 及其已知结合伙伴的相互作用模式，通过计算预测和实验验证潜在的 KRAS 相互作用蛋白。我们从所有实验确定的包含 KRAS 的蛋白质复合物中提取了 17 个 KRAS 相互作用基序作为查询，以使用我们内部的蛋白质-蛋白质相互作用预测方法 PPI-Miner 在人类蛋白质结构数据库中识别包含与查询结构相似片段的蛋白质。最后，在预测的 78 个 KRAS 潜在相互作用蛋白中，选择了 10 个进行实验验证，包括 BRAF，这是一种以前报道的相互作用蛋白，作为验证实验中的阳性对照。此外，还使用了一种已知与 KRAS 结合的肽 KRpep-2d 作为阳性对照。这 10 种蛋白质的预测相互作用基序被合成以进行生物层干涉测定，其中 4 种表现出与 KRAS 的结合亲和力，最强的 GRB10 被选为进一步验证。此外，还通过免疫荧光和共免疫沉淀证实了 GRB10（RA-PH 结构域）和 KRAS 之间的相互作用。
这些结果表明，我们的工作流程在预测 KRAS 的潜在相互作用蛋白方面是有效的，并加深了对 KRAS 驱动的肿瘤机制和治疗策略的开发的理解。
